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INFORMS
2000
128views more  INFORMS 2000»
15 years 7 months ago
A Revised Simplex Search Procedure for Stochastic Simulation Response Surface Optimization
We develop a variant of the Nelder-Mead (NM) simplex search procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering such dire...
David G. Humphrey, James R. Wilson
JAIR
2000
152views more  JAIR 2000»
15 years 7 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
ML
2000
ACM
244views Machine Learning» more  ML 2000»
15 years 7 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
ETS
2002
IEEE
146views Hardware» more  ETS 2002»
15 years 7 months ago
Teaching Motor Disability Assessment over the Web: MODASPECTRA
MODASPECTRA (MOtor Disability Assessment SPEcialists' TRAining) was a research and technology development project aimed at developing quality teaching and training of post-gr...
Salvatore Valenti, Sandro Fioretti, Maurizio Mauri...
NN
2000
Springer
159views Neural Networks» more  NN 2000»
15 years 7 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
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